The tool allows you to drill down by each physician and provides her rank within a state and specialty, the number of services she has performed, total and average payments by Medicare and how she has coded overall. It further provides information about each of the procedures billed to Medicare, # of unique visits by patients on whom the procedure was performed and so on.

What physicians who are letting their EHRs code for them are not realizing is this: by allowing the system to suggest codes (often higher codes) based on clicks over Physical Exam, Review of Systems and templatized SOAP and operative notes, they would need to be prepared to future public scrutiny that would peg them with peers across their county, state and the whole country. Imagine this in the context of ALL the data provided to CMS via Meaningful Use.

Medicine undergoes shifts every few decades – from germ theory to medications to reliance on clinical trials. During the past decade, there’s been a slow but steady shift towards reliance on data. Nearly every treatment plan has associated tests – radiology tests, pathology tests and possibly DNA and microbiome tests in the future. Doctors rely on data to confirm their hunches and to also protect themselves from law suits. Over the next decade, the amount of data we will get from a patient’s body is going to be enormous – akin to the amount of data we are now generally exposed to everyday as consumers. According to Marty Kohn from IBM’s Watson, 90% of the world’s data was created in the last two years and 1 trillion connected devices are generating 2.5 quintillion bytes of data every day (quintillion is 1 followed by 18 zeroes).

Doctors have a dual relationship with data. On one hand, they use it clinically for treatment (e.g. lab tests) where the data is of high value. On the other, when they document medical charts – they enter minimal information and enter standardized information (e.g. an operative note – almost no one reads this). The main reason for this polar relationship is because they aren’t visualizing the use or the value of the data that they put in. They don’t combine and use it as a whole to analyze their patient population. They don’t use it to predict future outcomes. In the future, they will.

Medicine is gradually migrating from an art to a more exact science. IBM Watson has been trained by senior oncologists at Kettering Institute to assist in diagnosing patients. If these trends are amplified, it might not be so difficult to imagine that a part of medicine could even become a data science – where algorithms analyze data from inside (e.g. DNA tests) and outside (e.g. activity trackers) and present findings to a doctor, who then reviews and confirms a diagnosis. If this were to become even remotely true, the value of data in medical charts would go up. So may be we must pause for a moment to consider what we put into a medical chart everyday.